import math

import flax.linen as nn
import jax.numpy as jnp


def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__ = 1    ,     a__ = 1    ,     a__ = 1.0e4    ,     a__ = False    ,     a__ = 1.0    ,     )      ->jnp.ndarray:




  '''simple docstring'''

  assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
  assert embedding_dim % 2 == 0, f'Embedding dimension {embedding_dim} should be even'
  _UpperCamelCase           =    float(embedding_dim // 2 )
  _UpperCamelCase           =    math.log(max_timescale / min_timescale ) / (num_timescales - freq_shift)
  _UpperCamelCase           =    min_timescale * jnp.exp(jnp.arange(a__    ,     dtype=jnp.floataa ) * -log_timescale_increment )
  _UpperCamelCase           =    jnp.expand_dims(a__    ,     1 ) * jnp.expand_dims(a__    ,     0 )

  # scale embeddings
  _UpperCamelCase           =    scale * emb

  if flip_sin_to_cos:
    _UpperCamelCase           =    jnp.concatenate([jnp.cos(a__ ), jnp.sin(a__ )]    ,     axis=1 )
  else:
    _UpperCamelCase           =    jnp.concatenate([jnp.sin(a__ ), jnp.cos(a__ )]    ,     axis=1 )
  _UpperCamelCase           =    jnp.reshape(a__    ,     [jnp.shape(a__ )[0], embedding_dim] )
  return signal




class 					_UpperCAmelCase			(     nn.Module  ):



 '''simple docstring'''




 __A			       =					32
 __A			       =					jnp.floataa







 @nn.compact
 def __call__(		self				:   Tuple							, lowercase_				:   Dict)						->	str:


   """simple docstring"""







   _UpperCamelCase           =    nn.Dense(self.time_embed_dim							, dtype=self.dtype							, name="linear_1")(lowercase_)
   _UpperCamelCase           =    nn.silu(lowercase_)
   _UpperCamelCase           =    nn.Dense(self.time_embed_dim							, dtype=self.dtype							, name="linear_2")(lowercase_)
   return temb




class 					_UpperCAmelCase			(     nn.Module  ):



 '''simple docstring'''




 __A			       =					32
 __A			       =					False
 __A			       =					1







 @nn.compact
 def __call__(		self				:   Any							, lowercase_				:   Tuple)						->	int:


   """simple docstring"""







   return get_sinusoidal_embeddings(
       lowercase_							, embedding_dim=self.dim							, flip_sin_to_cos=self.flip_sin_to_cos							, freq_shift=self.freq_shift)





from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version


def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__ = None )      ->str:




  '''simple docstring'''

  if version.parse(hfh.__version__ ).release < version.parse("0.11.0" ).release:
    # old versions of hfh don't url-encode the file path
    _UpperCamelCase           =    quote(a__ )
  return hfh.hf_hub_url(a__    ,     a__    ,     repo_type="dataset"    ,     revision=a__ )




